Year
2006
Abstract
While methodologies for assessing proliferation risk (or resistance) have advanced significantly over the past decade, current methodologies suffer from a range of flaws, such as over-reliance on subjective criteria, use of attribute sets that are incompatible with other methodologies, and a failure to identify, understand, or untangle dependencies existing between attributes. These flaws limit the reproducibility of results, the overall utility of methodologies, and restrict the application of sensitivity analyses. Many of these flaws may be addressed by strengthening the foundation upon which existing methodologies are built. To accomplish this, we propose developing a limited set of attributes that rely on measurable data as much as possible and avoid hidden correlations which may affect results.